In the field of personal fitness appliances and personal health care it is desirable to get insight into a body's proportional composition of different tissue types. For this purpose it is necessary to distinguish several main tissues from each other. The most important tissues to detect from a health perspective are: fat mass and fat-free mass, lean body mass and muscle mass and a further discrimination of adipose tissue in subcutaneous and intra-abdominal adipose tissue. Commonly used solutions to detect tissue layers in body tissues use either modalities that are too complex to be used in a home setting like MRI scan, under-water weighting and skin fold measurements that require proper training to be meaningful or modalities that are too inconsistent to provide meaningful data such as bioelectrical impedance, which is very sensitive to the varying amount of water in the body. Furthermore these techniques are only capable of determining total mass of the selected tissue and do not provide insight into “on the spot” thicknesses of certain tissues. Other techniques involve either measurement with multi-beam and multi-focus ultrasound devices, but this involves heavy processing and costly hardware or makes prior assumptions about where the tissue layer should be. Due to the huge variation in body composition across the population such techniques cannot be applied widely.
Measuring body fat using ultrasound devices is disclosed for example in U.S. Pat. No. 5,941,825. This method measures body fat by transmitting into a body ultrasound pulses, measuring at least one reflective distance, selecting the at least one reflective distance, which has the shortest distance to indicate the distance between the inner and outer border of subcutaneous fat tissue, wherein the selecting of the at least one reflective distance corrects for an ultrasound transmission parallax. It is asserted that this allows for a more convenient and precise measurement of layer thicknesses in an object.